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Open nowPosted 94 days ago

具身智能模型推理架构师

xiaopeng/index1,586 open roles

Where
Shenzhen, Guangdong, Chinese Mainland
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Your applicationOpen now具身智能模型推理架构师xiaopeng/index · Shenzhen, Guangdong, Chinese Mainland

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. xiaopeng/index postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: posted 94 days ago

xiaopeng/index median: 1 days open

The posting

1、主导具身智能模型推理系统的架构设计、核心开发与落地，制定模型运行、适配、优化和部署的整体技术方案； 2、建设统一的模型推理 Runtime 与服务框架，完善模型加载、执行、并发、生命周期管理及标准化接口，支撑不同模型快速接入； 3、建立模型压缩、量化与精度对齐能力，在性能、精度、内存与功耗之间进行系统优化，保障模型在小鹏自研芯片平台上的精度一致性与稳定运行； 4、设计端侧异构算力与多模型调度机制，优化 CPU、GPU、NPU 等计算资源的分配和协同，提升复杂任务下的资源利用率与推理效率； 5、从模型设计阶段介入部署可行性与性能评估，建设覆盖模型转换、量化、性能基准、端侧验证和发布的标准化工具链，协同算法、芯片及业务团队推动模型稳定量产。

1、计算机、人工智能、自动化等相关专业本科及以上学历； 2、具备端侧模型部署、推理框架、大模型推理服务、AI 芯片工具链或模型压缩优化中的一类或多类工程经验； 3、精通 C++，熟练使用 Python，具备扎实的 Linux 系统编程、并发编程和性能分析能力； 4、深入理解模型推理全流程，包括模型转换、运行时执行、内存管理、并发调度、性能评测及问题诊断； 5、在以下至少一个方向具备深入经验： 推理 Runtime、内存管理或并发执行优化； PTQ、QAT、混合精度等模型量化与精度对齐； 嵌入式 NPU 模型适配、部署与性能优化； 异构资源调度、内存优化或多模型协同运行； 6、理解 Transformer、VLM、VLA 等模型的计算与访存特性，能够结合硬件特点分析性能瓶颈； 7、有复杂模型从算法原型到产品部署的完整实践，能够协同算法、芯片和业务团队推动量产落地。

加分项： 有机器人、自动驾驶或智能硬件端侧推理平台建设经验； 有 VLM、VLA、多模态模型或端侧语言模型部署与优化经验； 熟悉 vLLM、SGLang、TensorRT-LLM、llama.cpp、MLC LLM 等大模型推理框架，或有主流芯片大模型推理 SDK 使用与优化经验； 熟悉 KV Cache 管理、连续批处理、推测解码等大模型推理优化技术； 有自研或嵌入式芯片平台适配、功耗优化、模型部署工具链或自动化精度回归体系建设经验。

我们期望你具备的特质： 系统权衡能力：能够在性能、精度、内存、功耗与交付效率之间做出合理取舍； 工程落地能力：能够深入模型、运行时和硬件平台定位问题，将优化方案稳定落到产品中； 协同推动能力：能够连接算法、芯片与业务团队，推动模型从原型验证走向规模化部署。

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